A Statistical Shape Model of Infrarenal Aortic Necks in Patients With and Without Late Type Ia Endoleak After Endovascular Aneurysm Repair

Author:

van Veldhuizen Willemina A.1ORCID,Schuurmann Richte C. L.12,Zuidema Roy1ORCID,Geraedts Anna C. M.3ORCID,IJpma Frank F. A.4,Kropman Rogier H. J.5,Antoniou George A.67ORCID,van Sambeek Marc R. H. M.8,Balm Ron3,Wolterink Jelmer M.9,de Vries Jean-Paul P. M.1

Affiliation:

1. Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, Groningen, The Netherlands

2. Multi-Modality Medical Imaging (M3I) Group, Technical Medical Centre, University of Twente, Enschede, The Netherlands

3. Department of Surgery, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands

4. Department of Surgery, Division of Trauma Surgery, University Medical Center Groningen, Groningen, The Netherlands

5. Department of Vascular Surgery, St. Antonius Hospital, Nieuwegein, The Netherlands

6. Department of Vascular and Endovascular Surgery, Manchester University NHS Foundation Trust, Manchester, UK

7. Division of Cardiovascular Sciences, School of Medical Sciences, Manchester Academic Health Science Centre, The University of Manchester, Manchester, UK

8. Department of Vascular Surgery, Catharina Hospital, Eindhoven, The Netherlands

9. Department of Applied Mathematics, Technical Medical Centre, University of Twente, Enschede, The Netherlands

Abstract

Purpose: Hostile aortic neck characteristics, including short length, severe suprarenal and infrarenal angulation, conicity, and large diameter, have been associated with increased risk for type Ia endoleak (T1aEL) after endovascular aneurysm repair (EVAR). This study investigates the mid-term discriminative ability of a statistical shape model (SSM) of the infrarenal aortic neck morphology compared with or in combination with conventional measurements in patients who developed T1aEL post-EVAR. Materials and Methods: The dataset composed of EVAR patients who developed a T1aEL during follow-up and a control group without T1aEL. Principal component (PC) analysis was performed using a parametrization to create an SSM. Three logistic regression models were created. To discriminate between patients with and without T1aEL, sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC) were calculated. Results: In total, 126 patients (84% male) were included. Median follow-up time in T1aEl group and control group was 52 (31, 78.5) and 51 (40, 62.5) months, respectively. Median follow-up time was not statistically different between the groups (p=0.72). A statistically significant difference between the median PC scores of the T1aEL and control groups was found for the first, eighth, and ninth PC. Sensitivity, specificity, and AUC values for the SSM-based versus the conventional measurements–based logistic regression models were 79%, 70%, and 0.82 versus 74%, 73%, and 0.85, respectively. The model of the SSM and conventional measurements combined resulted in sensitivity, specificity, and AUC of 81%, 81%, and 0.92. Conclusion: An SSM of the infrarenal aortic neck determines its 3-dimensional geometry. The SSM is a potential valuable tool for risk stratification and T1aEL prediction in EVAR. The SSM complements the conventional measurements of the individual preoperative infrarenal aortic neck geometry by increasing the predictive value for late type Ia endoleak after standard EVAR. Clinical Impact A statistical shape model (SSM) determines the 3-dimensional geometry of the infrarenal aortic neck. The SSM complements the conventional measurements of the individual pre-operative infrarenal aortic neck geometry by increasing the predictive value for late type Ia endoleaks post-EVAR. The SSM is a potential valuable tool for risk stratification and late T1aEL prediction in EVAR and it is a first step toward implementation of a treatment planning support tool in daily clinical practice.

Publisher

SAGE Publications

Subject

Cardiology and Cardiovascular Medicine,Radiology, Nuclear Medicine and imaging,Surgery

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